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Found 2 papers, 1 papers with code
Understanding Impact of Human Feedback via Influence Functions
By quantifying the impact of human feedback on reward models, we believe that influence functions can enhance feedback interpretability and contribute to scalable oversight in RLHF, helping labelers provide more accurate and consistent feedback.
Benchmarking Mobile Device Control Agents across Diverse Configurations
In this work, we introduce B-MoCA: a novel benchmark with interactive environments for evaluating and developing mobile device control agents.
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